/external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
H A D | lrn_ops.cc | 57 auto scale = builder->Pow( variable 62 ctx->SetOutput(0, builder->Mul(input, scale));
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/external/tensorflow/tensorflow/compiler/xla/ |
H A D | index_util.cc | 78 int64 scale = 1; local 85 scale = shape.dimensions(dimension); 88 linear_index += scale * multi_index[dimension]; 89 scale *= shape.dimensions(dimension);
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/external/tensorflow/tensorflow/contrib/distributions/python/ops/bijectors/ |
H A D | affine.py | 45 """Compute `Y = g(X; shift, scale) = scale @ X + shift`. 47 Here `scale = c * I + diag(D1) + tril(L) + V @ diag(D2) @ V.T`. 49 In TF parlance, the `scale` term is logically equivalent to: 52 scale = ( 61 The `scale` term is applied without necessarily materializing constituent 112 This `Bijector` is initialized with `shift` `Tensor` and `scale` arguments, 116 Y = g(X) = scale @ X + shift 119 where the `scale` term is logically equivalent to: 122 scale 347 def scale(self): member in class:Affine [all...] |
H A D | affine_linear_operator.py | 38 """Compute `Y = g(X; shift, scale) = scale @ X + shift`. 40 `shift` is a numeric `Tensor` and `scale` is a `LinearOperator`. 42 If `X` is a scalar then the forward transformation is: `scale * X + shift` 47 before being premultiplied by `scale`: 62 premultiplying by `scale`, we take the inverse of this procedure. The input 64 `inv(scale)`. 75 scale = linalg.LinearOperatorDiag(diag) 76 affine = AffineLinearOperator(shift, scale) 78 # y = scale 185 def scale(self): member in class:AffineLinearOperator [all...] |
/external/tensorflow/tensorflow/contrib/distributions/python/ops/ |
H A D | mvn_linear_operator.py | 61 `scale` matrix; `covariance = scale @ scale.T`, where `@` denotes 69 pdf(x; loc, scale) = exp(-0.5 ||y||**2) / Z, 70 y = inv(scale) @ (x - loc), 71 Z = (2 pi)**(0.5 k) |det(scale)|, 77 * `scale` is a linear operator in `R^{k x k}`, `cov = scale @ scale.T`, 81 The MultivariateNormal distribution is a member of the [location-scale 204 def scale(self): member in class:MultivariateNormalLinearOperator [all...] |
H A D | vector_exponential_linear_operator.py | 55 `scale` matrix: `covariance = scale @ scale.T`, where `@` denotes 63 pdf(y; loc, scale) = exp(-||x||_1) / Z, for y in S(loc, scale), 64 x = inv(scale) @ (y - loc), 65 Z = |det(scale)|, 71 * `scale` is a linear operator in `R^{k x k}`, `cov = scale @ scale 208 def scale(self): member in class:VectorExponentialLinearOperator [all...] |
H A D | vector_laplace_linear_operator.py | 60 `scale` matrix: `covariance = 2 * scale @ scale.T`, where `@` denotes 68 pdf(x; loc, scale) = exp(-||y||_1) / Z, 69 y = inv(scale) @ (x - loc), 70 Z = 2**k |det(scale)|, 76 * `scale` is a linear operator in `R^{k x k}`, `cov = scale @ scale.T`, 80 The VectorLaplace distribution is a member of the [location-scale 225 def scale(self): member in class:VectorLaplaceLinearOperator [all...] |
/external/tensorflow/tensorflow/core/kernels/ |
H A D | fake_quant_ops_functor.h | 43 float* nudged_min, float* nudged_max, float* scale) { 46 *scale = (max - min) / (quant_max_float - quant_min_float); 47 const float zero_point_from_min = quant_min_float - min / *scale; 59 *nudged_min = (quant_min_float - nudged_zero_point) * (*scale); 60 *nudged_max = (quant_max_float - nudged_zero_point) * (*scale); 41 Nudge( const float min, const float max, const int quant_min, const int quant_max, float* nudged_min, float* nudged_max, float* scale) argument
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H A D | relu_op_functor.h | 138 const auto scale = static_cast<T>(1.0507009873554804934193349852946); local 145 scale * features); 160 const auto scale = static_cast<T>(1.0507009873554804934193349852946); local 164 .select(gradients * (activations + scale_alpha), gradients * scale);
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/external/webrtc/webrtc/modules/audio_coding/codecs/isac/fix/source/ |
H A D | filters.c | 21 int16_t* __restrict scale) { 57 *scale = scaling; 17 WebRtcIsacfix_AutocorrC(int32_t* __restrict r, const int16_t* __restrict x, int16_t N, int16_t order, int16_t* __restrict scale) argument
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H A D | filters_mips.c | 19 int16_t* __restrict scale) { 362 *scale = scaling; 15 WebRtcIsacfix_AutocorrMIPS(int32_t* __restrict r, const int16_t* __restrict x, int16_t N, int16_t order, int16_t* __restrict scale) argument
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H A D | filters_neon.c | 22 int16_t* __restrict scale) { 110 *scale = scaling; 18 WebRtcIsacfix_AutocorrNeon(int32_t* __restrict r, const int16_t* x, int16_t n, int16_t order, int16_t* __restrict scale) argument
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/external/webrtc/webrtc/modules/audio_coding/neteq/ |
H A D | background_noise.h | 99 scale = 20000; 110 int16_t scale; member in struct:webrtc::BackgroundNoise::ChannelParameters
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/external/ImageMagick/coders/ |
H A D | jnx.c | 102 scale; 207 jnx_level_info[i].scale=ReadBlobLSBLong(image); 99 scale; member in struct:_JNXLevelInfo
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/external/aac/libFDK/include/ |
H A D | FDK_trigFcts.h | 137 FIXP_DBL fixp_cos(FIXP_DBL x, int scale); 138 FIXP_DBL fixp_sin(FIXP_DBL x, int scale); 155 static inline FIXP_DBL fixp_sin_cos_residual_inline(FIXP_DBL x, int scale, argument 160 int shift = (31 - scale - LD - 1); 169 residual <<= scale; local 209 /* scale down by 1 for overflow prevention. This is undone at the calling 224 * \param scale exponent of x1 and x2 229 const int scale, FIXP_DBL *out) { 231 residual = fixp_sin_cos_residual_inline(x1, scale, &sine, &cosine); 244 residual = fixp_sin_cos_residual_inline(x2, scale, 228 inline_fixp_cos_sin(FIXP_DBL x1, FIXP_DBL x2, const int scale, FIXP_DBL *out) argument [all...] |
H A D | qmf_pcm.h | 145 int scale = (DFRACT_BITS - SAMPLE_BITS_QMFOUT) - 1 - qmf->outScalefactor - local 157 if (scale > 0) { 158 if (scale < (DFRACT_BITS - 1)) 159 rnd_val = FIXP_DBL(1 << (scale - 1)); 161 scale = (DFRACT_BITS - 1); 163 scale = fMax(scale, -(DFRACT_BITS - 1)); 183 if (scale >= 0) { 189 SATURATE_RIGHT_SHIFT(Are + rnd_val, scale, SAMPLE_BITS_QMFOUT)); 192 SATURATE_LEFT_SHIFT(Are, -scale, SAMPLE_BITS_QMFOU 237 int scale = (DFRACT_BITS - SAMPLE_BITS_QMFOUT) - 1 - qmf->outScalefactor - local [all...] |
/external/aac/libFDK/src/ |
H A D | FDK_trigFcts.cpp | 205 /* ==> set q on fixed scale level as desired from fixp_atan() */ 299 FIXP_DBL fixp_cos(FIXP_DBL x, int scale) { argument 302 residual = fixp_sin_cos_residual_inline(x, scale, &sine, &cosine); 313 FIXP_DBL fixp_sin(FIXP_DBL x, int scale) { argument 316 residual = fixp_sin_cos_residual_inline(x, scale, &sine, &cosine); 326 void fixp_cos_sin(FIXP_DBL x, int scale, FIXP_DBL *cos, FIXP_DBL *sin) { argument 329 residual = fixp_sin_cos_residual_inline(x, scale, &sine, &cosine);
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/external/aac/libSACenc/src/ |
H A D | sacenc_staticgain.cpp | 255 const HANDLE_STATIC_GAIN_CONFIG hStaticGainConfig, INT *const scale) { 275 *scale = 0; 282 *scale = GAINCF_SF - s; 336 const INT nOutputSamples, const INT scale) { 345 if (scale < 0) { 348 pOutputSamples[i] = pOutputSamples[i] >> (-scale); 353 fMult(postGain, FX_PCM2FX_DBL(pOutputSamples[i])) >> (-scale)); 360 FX_PCM2FX_DBL(pOutputSamples[i]), scale, DFRACT_BITS)); 365 fMult(postGain, FX_PCM2FX_DBL(pOutputSamples[i])), scale, 253 fdk_sacenc_staticGain_Init( HANDLE_STATIC_GAIN hStaticGain, const HANDLE_STATIC_GAIN_CONFIG hStaticGainConfig, INT *const scale) argument 334 fdk_sacenc_staticPostGain_ApplyFDK( const HANDLE_STATIC_GAIN hStaticGain, INT_PCM *const pOutputSamples, const INT nOutputSamples, const INT scale) argument
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/external/androidplot/Examples/DemoApp/src/com/androidplot/demos/ |
H A D | TouchZoomExampleActivity.java | 82 int scale = 1;
83 for (int i = 0; i < 4; i++, scale *= 5) {
85 populateSeries(series[i], scale);
165 private void zoom(float scale) {
argument 168 float offset = domainSpan * scale / 2.0f;
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/external/apache-commons-math/src/main/java/org/apache/commons/math/distribution/ |
H A D | CauchyDistributionImpl.java | 48 /** The scale of this distribution. */ 49 private double scale = 1; field in class:CauchyDistributionImpl 55 * Creates cauchy distribution with the medain equal to zero and scale 63 * Create a cauchy distribution using the given median and scale. 65 * @param s scale parameter for this distribution 72 * Create a cauchy distribution using the given median and scale. 74 * @param s scale parameter for this distribution 92 return 0.5 + (FastMath.atan((x - median) / scale) / FastMath.PI); 104 * Access the scale parameter. 105 * @return scale paramete [all...] |
H A D | WeibullDistributionImpl.java | 49 /** The scale parameter. */ 50 private double scale; field in class:WeibullDistributionImpl 68 * Creates weibull distribution with the given shape and scale and a 71 * @param beta the scale parameter. 78 * Creates weibull distribution with the given shape, scale and inverse 81 * @param beta the scale parameter. 103 ret = 1.0 - FastMath.exp(-FastMath.pow(x / scale, shape)); 117 * Access the scale parameter. 118 * @return the scale parameter. 121 return scale; [all...] |
/external/apache-commons-math/src/main/java/org/apache/commons/math/ode/nonstiff/ |
H A D | AdaptiveStepsizeIntegrator.java | 209 * @param scale scaling vector for the state vector (can be shorter than state vector) 220 final boolean forward, final int order, final double[] scale, 230 // very rough first guess : h = 0.01 * ||y/scale|| / ||y'/scale|| 235 for (int j = 0; j < scale.length; ++j) { 236 ratio = y0[j] / scale[j]; 238 ratio = yDot0[j] / scale[j]; 256 for (int j = 0; j < scale.length; ++j) { 257 ratio = (yDot1[j] - yDot0[j]) / scale[j]; 219 initializeStep(final FirstOrderDifferentialEquations equations, final boolean forward, final int order, final double[] scale, final double t0, final double[] y0, final double[] yDot0, final double[] y1, final double[] yDot1) argument
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H A D | GraggBulirschStoerStepInterpolator.java | 294 * @param scale scaling array 297 public double estimateError(final double[] scale) { argument 300 for (int i = 0; i < scale.length; ++i) { 301 final double e = polynoms[currentDegree][i] / scale[i]; 304 error = FastMath.sqrt(error / scale.length) * errfac[currentDegree - 5];
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/external/apache-commons-math/src/main/java/org/apache/commons/math/util/ |
H A D | BigReal.java | 55 /*** BigDecimal scale ***/ 56 private int scale = 64; field in class:BigReal 74 * @param scale scale to use 76 public BigReal(BigInteger unscaledVal, int scale) { argument 77 d = new BigDecimal(unscaledVal, scale); 82 * @param scale scale to use 85 public BigReal(BigInteger unscaledVal, int scale, MathContext mc) { argument 86 d = new BigDecimal(unscaledVal, scale, m 225 setScale(int scale) argument [all...] |
/external/autotest/client/deps/glbench/src/ |
H A D | fillratetest.cc | 54 "uniform float scale;" 57 " gl_Position = position * vec4(scale, scale, 1., 1.);" 124 GLuint scale_uniform = glGetUniformLocation(program, "scale"); 134 float scale = 0.7071f; local 135 glUniform1f(scale_uniform, scale); 142 scale = 0.758f; 143 glUniform1f(scale_uniform, scale); 150 scale = 0.933f; 151 glUniform1f(scale_uniform, scale); [all...] |